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» Learning from Multiple Annotators with Gaussian Processes
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ICCV
2011
IEEE
12 years 7 months ago
From Learning Models of Natural Image Patches to Whole Image Restoration
Learning good image priors is of utmost importance for the study of vision, computer vision and image processing applications. Learning priors and optimizing over whole images can...
Daniel Zoran, Yair Weiss
CLEF
2010
Springer
13 years 8 months ago
Detection of Visual Concepts and Annotation of Images Using Predictive Clustering Trees
Abstract. In this paper, we present a multiple targets classification system for visual concepts detection and image annotation. Multiple targets classification (MTC) is a variant ...
Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, ...
CORR
2006
Springer
95views Education» more  CORR 2006»
13 years 7 months ago
Optimal Distortion-Power Tradeoffs in Gaussian Sensor Networks
We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. The overall goal of the sensor network is to take measurements ...
Nan Liu, Sennur Ulukus
BMCBI
2005
189views more  BMCBI 2005»
13 years 7 months ago
A sentence sliding window approach to extract protein annotations from biomedical articles
Background: Within the emerging field of text mining and statistical natural language processing (NLP) applied to biomedical articles, a broad variety of techniques have been deve...
Martin Krallinger, Maria Padron, Alfonso Valencia
CVPR
2009
IEEE
1599views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Multi-Label Sparse Coding for Automatic Image Annotation
In this paper, we present a multi-label sparse coding framework for feature extraction and classification within the context of automatic image annotation. First, each image is ...
Changhu Wang (University of Science and Technology...